In this paper we analyze rank assignments and promotions of a
group of Federal civilian employees. with special attention to racial
differences. To do so, we estimate a multinomial logit model. using
pooled data from four different years, on the civilian employees of a
large U.S. Army base in the southeastern United States. We derive
implications of the estimated parameters concerning the effects of a
number of employee characteristics on the relative likelihood of a
person's being in the various ranks. To measure the effect of race on
rank assignments and promotions, we use a simulation method that
provides information for a polytomous discrete dependent variable that
is equivalent to that given by a linear regression coefficient for a
continuous dependent variable.
_Our application of the multinomial logit model to pooled time
series cross section data assumes that the stochastic error terms are
independently distributed. across persons and ranks and over time. We
test the adequacy of this assumption for analyzing three aspects of
ranking and promotions: 1) the rank distribution of employees at a
given time, 2) shifts over time in the aggregate rank distribution of a
cohort of employees, and 3) rank-to-rank movements of individual
employees over time. We find that the model performs adequately in the
first two cases, but fails in the third.